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Found 11 papers, 2 papers with code
Adult learners recall and recognition performance and affective feedback when learning from an AI-generated synthetic video
However, there are a limited number of well-designed experimental studies investigating the impact of learning gains and affective feedback from AI-generated media compared to traditional media (e. g., text from documents and human recordings of video).
Frequency and Generalisation of Periodic Activation Functions in Reinforcement Learning
One is that periodic activations learn low frequency representations and as a result avoid overfitting to bootstrapped targets.
Predictive representations: building blocks of intelligence
Adaptive behavior often requires predicting future events.
Probing neural representations of scene perception in a hippocampally dependent task using artificial neural networks
Deep artificial neural networks (DNNs) trained through backpropagation provide effective models of the mammalian visual system, accurately capturing the hierarchy of neural responses through primary visual cortex to inferior temporal cortex (IT).
Functional Connectome: Approximating Brain Networks with Artificial Neural Networks
We show that trained deep neural networks are able to perform zero-shot generalisation in novel environments, and allows for a wealth of tasks such as decoding the animal's location in space with high accuracy.
Temporally Extended Successor Representations
We show that in environments with dynamic reward structure, t-SR is able to leverage both the flexibility of the successor representation and the abstraction afforded by temporally extended actions.
Using Forwards-Backwards Models to Approximate MDP Homomorphisms
Reinforcement learning agents must painstakingly learn through trial and error what sets of state-action pairs are value equivalent -- requiring an often prohibitively large amount of environment experience.
Interpreting wide-band neural activity using convolutional neural networks
Rapid progress in technologies such as calcium imaging and electrophysiology has seen a dramatic increase in the size and extent of neural recordings.
How to Stay Curious while Avoiding Noisy TVs using Aleatoric Uncertainty Estimation
Exploration in environments with sparse rewards is difficult for artificial agents.
MEMO: A Deep Network for Flexible Combination of Episodic Memories
First, it introduces a separation between memories (facts) stored in external memory and the items that comprise these facts in external memory.
Generalisation of structural knowledge in the hippocampal-entorhinal system
We propose that to generalise structural knowledge, the representations of the structure of the world, i. e. how entities in the world relate to each other, need to be separated from representations of the entities themselves.
